Health & Pharma

AI in Healthcare: Make Your Organization AI Ready

by CiarŠn Daly
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by Mike McNamara


LONDON - AI is poised to transform industry by using advanced data-based learning to identify patterns, develop predictive insights, and enable increasingly accurate autonomous systems.

AI offers the promise of faster and more customized pharmaceutical development, more effective fraud detection for insurers, the opportunity to†reduce physician burn-out with improved electronic health record†(EHR) workflows, and other operational efficiencies that will vastly increase productivity, help manage costs of care, and, of course, speed the development of new treatments and therapies.

There are two requirements for organizations to be successful in integrating AI into clinical workflows and research and development. The first is access to large amounts of data and the second is that this data is usable, accessible, and protected. While healthcare organizations have no trouble meeting the first requirement with petabytes of data created each day, nearly all organizations, regardless of industry, struggle with data usability, accessibility, portability, and security.


Related: The AI will see you now - machine learning in healthcare


A robust AI infrastructure needs to be flexible and future-proof to enable the organization to unlock the potential of data science on their AI journey from predictive analytics to autonomous decision making.

A key aspect of an AI-ready infrastructure is the ability to
succeed without the limitations of where data resides. The infrastructure must
enable an integrated data pipeline across edge, core, and cloud and streamline
the flow of data from ingest, to prep, to training, and inference. It must
support seamless, cost effective movement of data across on-premise and clouds.

AI isnít about machines churning out answers, itís about unlocking the value of data. Itís about developing insights and knowledge that can be put to work for the good of the patient and provider that were previously unrealistic in terms of time and complexity.

Learn more about building AI-ready data environments here


Join Mike and the NetApp team at The AI Summit London 2019, June 12-13. Find out more

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